Brain Age Is Longitudinally Associated With Sensorimotor Impairment and Mild Cognitive Impairment in Subacute Stroke
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND Brain age, a proxy of overall brain health estimated from structural neuroimaging, has been associated with sensorimotor performance in chronic stroke. Similarly, post-stroke cognitive outcomes have been associated with accelerated brain aging. However, the relationships between brain age, sensorimotor, and cognitive outcomes in early subacute stroke (<3 months after onset) are less understood. METHODS In this work, we investigated associations between stroke survivors’ brain-predicted age difference (brain-PAD, quantified as a person’s brain age minus their chronological age) and longitudinal measurements of motor impairment (Fugl-Meyer Upper Extremity Assessment [FMUE]) and cognitive impairment (Montreal Cognitive Assessment [MoCA]) in subacute stroke. We used high-resolution T1-weighted MRIs from 44 participants at baseline and three months after stroke onset to investigate associations between brain-PAD, MoCA, and FMUE scores with robust linear mixed-effects regression models and mediation analyses. RESULTS We found negative associations between baseline brain-PAD and FMUE at baseline (β=-0.87, p=0.029) and three months (β=-0.87, p=0.011). Baseline brain-PAD was also negatively correlated with MoCA at three months (β=-0.13, p=0.015) but not at baseline (β=-0.11, p=0.141). Baseline brain-PAD was not associated with changes in FMUE (β=-0.01, p=0.930) or MoCA (β=-0.03, p=0.579). Finally, MoCA was not associated with FMUE at either time point, nor did it mediate the relationship between brain-PAD and FMUE. CONCLUSION Overall, we show that baseline brain age predicts both motor and cognitive outcomes at three months. However, motor and cognitive outcomes are not directly associated with one other. This suggests that brain age is representative of changes in multiple, distinct neurological pathways post-stroke. Further research with longer time intervals is needed to examine whether brain age also predicts chronic stroke outcomes.
Authors: Octavio Marin-Pardo, Mahir H. Khan, Stuti Chakraborty, Michael R. Borich, Mayerly Castillo, James H. Cole, Steven C. Cramer, Miranda R. Donnelly, Emily E. Fokas, Niko H. Fullmer, Jeanette R. Gumarang, Leticia Hayes, Hosung Kim, Amisha Kumar, Emily. A. Marks, Emily R. Rosario, Heidi M. Schambra, Nicolas Schweighofer, Grace C. Song, Myriam Taga, Bethany P. Tavenner, Carolee Winstein, Sook-Lei Liew
Institutions: University of Southern California, Emory University, California State University, Fullerton, University College London, University of California, Los Angeles, Towson University, NYU Langone Health, New York University, Casa Colina Centers for Rehabilitation, University of California, Riverside
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,810
Awards: Effects of global brain health on sensorimotor recovery after stroke, A Data Science Approach To Personalizing Sensorimotor Training Post-Stroke, Global Brain Health Predictors of Post-Stroke Sensorimotor Recovery using AI-Enhanced Clinical MRIs, Data Science and Analytics for Precision Rehabilitation (DAPR) Center
OpenAlex ID: W4415148556